Theme 4: Quantitative Research

The Role of Internet User- Characteristics and Motives in Explaining Three Dimensions of Internet Addiction (Kim and Haridakis, 2009)

Published in: the Journal of Computer-Mediated Communication ( Impact Factor: 1.778)

The researchers examined how users' background characteristics, motives, and the amount of Internet use contribute to Internet addiction. They identified three possible dimensions of internet addiction: intrusion, escaping reality and attachment. The results suggest that motives and users’ background are important potential factors to internet addiction.

The sample included 203 undergraduate students and the study took place in the USA. All participants were required to use internet.

The quantitative methodologies and measurements used in this study were designed based on previous studies, mainly on addiction in substance and media related contents-Internet and television. The participants answered questionnaires with the following measurements: Internet addiction, time spent using Internet, motives for using Internet and their background characteristics-locus of control, participants' self-esteem, shyness, loneliness and sensation-seeking.

The benefits of using these questionnaires with various scales is that the researchers were able to collect quantitative data so that they could test and prove their hypotheses on the role of internet users’ characteristics and motives in internet addiction. Then, hierarchical regression analyses were used to examine the contribution of users' background characteristics, motives, and the amount of Internet use to predicting each of the three dimensions of Internet addiction that was identified: Intrusion, escaping reality, and attachment.

A limitation of the methodologies used is that the findings of this study on college students cannot be generalized, since only one community was examined. Furthermore, the researchers state that Internet evolving use and functions may require more up-to-date measures of variables (Ibid: 1009).   

While these scales and the reasoning for using them, as well as how the quantitative data of this study were worked is thoroughly explained, it is not clearly specified if the participants replied to these questions online or on written papers.

What I learned about quantitative methods from this paper is that no matter how well research methodologies and measurements are designed and even though statistical data are valuable, when they depend on humans living in a specific context, it is difficult to generalize the results. When it comes to social sciences, further research is necessary. Plus, the collected data, their presentation and interpretation depend heavily on the researchers’ agendas and the design of the methodology.

The main methodological problems of this study is that some of these measurements were outdated. More up-to-date measurements might be more appropriate. Furthermore, the results cannot be generalized since only one specific community was examined. If more communities were researched, we might have different data.

Physical activity, stress, and self-reportedupper respiratory tract infection (Fondell et al., 2010)

This paper examines the relationship between physical activity and self-reported upper respiratory tract infection (URTI) and the possible interactive relationship between physical activity, perceived stress and self-reported URTI. The study population was 1509 Swedish men and women aged 20-60. Quantitative data were collected from online questionnaires and follow up questionnaires that lasted 4 months. According to the results high levels of physical activity were associated with a reduced risk of self-reported URTI for both sexes. Additionally, highly stressed men appeared to benefit more from high levels of physical activity than people with lower stress.

The benefits of using quantitative methods is that the researchers can test a hypothesis. If the statistical and quantitative data agree with this hypothesis, the researchers can prove it. If not, the results might lead to something unexpected, to something that was not thought of before; it might lead to the understanding of a gap that could be researched in the future.

On the other hand, statistical data are just data. They do not provide understanding or explanation of something. Analysis and interpretation of the data is necessary. Plus, the design and implementation of a quantitative methodology demands time and effort; many people can be involved in this process. In order to be able to generalize the results, the study population should be large and representative of the general population. This is not an easy task. Generalization is not always possible since the population examined in a specific one, so further research is also necessary. It could be necessary to have follow up periods on even follow up studies.

The benefits of using qualitative methods, such as interviews and focus groups, is that they can provide a deeper and better understanding of something. The group of people examined is strictly specified.

On the other hand, since we are talking about a specific target group, the results might differ if we conduct the survey in another context or in 10 years. Another limitation is that researchers cannot interview a large population. Plus, it might be necessary to test and support with quantitative methodologies the results.    

REFERENCES

Fondell, E., Lagerros, Y. T., Sundberg, C. J., Lekander, M., Bälter, O., Rothman, K., & Bälter, K. (2010). Physical activity, stress, and self-reported upper respiratory tract infection. Med Sci Sports Exerc, 43(2), 272-279.

Kim, J. and Haridakis, P. M. (2009), The Role of Internet User Characteristics and Motives in Explaining Three Dimensions of Internet Addiction. Journal of Computer-Mediated Communication, 14: 988–1015. doi: 10.1111/j.1083-6101.2009.01478.x